Doctor of Philosophy (PhD)
Department of Leadership and Human Resource Development
The primary purpose of this study was to determine the relationship between selected social network characteristics and engagement among faculty at a research university (RU/VH). In 2013, a restructuring initiative targeted seven departments from different colleges at a public research university (RU/VH) located in the Gulf Coast region of the United States with a student population of more than 30,000. These departments were restructured to form a new academic college within the university. The archival sample for this study includes the faculty of the newly formed college who were in attendance at the initial college faculty meeting.
Network data were collected using a roster-recall methodology and engagement data were collected using the Utrecht Work Engagement Scale (UWES-9). Of the 184 potential respondents, 71 responded to the survey, resulting in a response rate of 38.6%. Of those responding, the completion rate was 95.8%, yielding 67 usable cases. Network size and centrality were both highly variable. Size ranged from 3 to 47; with a mean of 21.54 (SD = 9.657). Centrality ranged from .461 to 2.699, with a mean of 1.552 (SD = .5446). A comparison of mean values for engagement found that the sample values were consistently and significantly higher than the published norms (Ego Engagement - t=8.39, df=66, p < .001 and Mean Alter Engagement - t=33.89, df=66, p < .001).
Based on these findings the researcher concluded that the low response rate was most likely the result of deliberate non-participation on the part of some faculty members in the sample. The resulting selection bias appears to have affected the study variables in an assortment of ways: Social network size was decreased, ego engagement scores were increased, and Social network centrality was rendered unreliable by non-response. Non-participation could be reasonably interpreted as a sort of protest vote against the organizational change and the paradoxically high engagement scores would then indicate that the organizational change was highly unpopular. Thus, decision making based on the raw data would have grossly over-estimated the popularity of the restructuring.
Gibeson, Glenn M. IV, "Leveraging the Social Network to Support Engagement in an Academic Environment" (2017). LSU Doctoral Dissertations. 4130.